The success of bioinformatics in recent years has been prompted by
research in molecular biology and medicine in initiatives like the
human genome project. These initiatives gave rise to an enormous
increase in the volume and diversification of data, including protein
and genomic sequences, high-throughput experimental and biomedical
literature. The widespread availability of low-cost, full genome
sequencing, will introduce new challenges to bioinformatics as a key field to enable personalized medicine. New
methods are needed to realize the potential of personalized medicine:
(i) processing large-scale robust genomic data; (ii) interpreting the
functional effect and the impact of genomic variation; (iii)
integrating systems data to relate complex genetic interactions with
phenotypes; and (iv) translating these discoveries into medical
practice.

Systems Biology is a related field, devoted mainly to
efforts in cell modeling, that requires the coordinated efforts of
biological researchers with those related to data analysis,
mathematical modeling, computer simulation and optimization.

The accumulation and exploitation of large-scale databases prompts
for new computational technologies and for research into these
issues. In this context, many widely successful computational models
and tools used by biologists in these initiatives, such as clustering
and classification methods for experimental data, are based on
Artificial Intelligence (AI) techniques.

In fact, these methods have been helping in tasks related to knowledge
discovery, modeling and optimization tasks, aiming at the development
of computational models so that the response of biological complex
systems to any perturbation can be predicted. Hence, this workshop
brings the opportunity to discuss applications of AI with an
interdisciplinary character, exploring the interactions between
sub-areas of AI, Bioinformatics and Systems Biology.

Submissions should address relevant biological/ biomedical research problems, through computational techniques, making original
contributions at the fundamental or applied levels.

Paper submission
________________

Submitted papers should be full-length papers with a maximum length of
12 pages. The best papers will be published in a volume of Lecture
Notes in Artificial Intelligence (LNAI) by Springer (proceedings
indexed by the Thomson ISI Web of Knowledge). All other accepted
papers will be published in the local proceedings.

All papers should be submitted in PDF format through EPIA’2015
Conference Management Website:
http://epia2015.dei.uc.pt/call-for-papers/

All papers should be prepared according to the formatting instructions
of Springer LNAI series. The review process is
double-blind. Therefore, authors must remove their names from the
submitted papers and should take reasonable care not to indirectly
disclose their identity. References to own work may be included in
the paper, as long as referred to in the third person. Three program
committee members will be assigned to review each paper. Acceptance
will be based on the paper’s significance, technical quality, clarity,
relevance and originality. Accepted papers must be presented at the
conference by one of the authors and at least one author of each
accepted paper must register for the conference.